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Temporal limitations of the standard leaky integrate and fire model

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dc.contributor Aalto-yliopisto fi
dc.contributor Aalto University en
dc.contributor.author Merzon, Liya
dc.contributor.author Malevich, Tatiana
dc.contributor.author Zhulikov, Georgiy
dc.contributor.author Krasovskaya, Sofia
dc.contributor.author Macinnes, W. Joseph
dc.date.accessioned 2020-02-12T10:48:38Z
dc.date.available 2020-02-12T10:48:38Z
dc.date.issued 2020-01-01
dc.identifier.citation Merzon , L , Malevich , T , Zhulikov , G , Krasovskaya , S & Macinnes , W J 2020 , ' Temporal limitations of the standard leaky integrate and fire model ' , BRAIN SCIENCES , vol. 10 , no. 1 , 16 . https://doi.org/10.3390/brainsci10010016 en
dc.identifier.issn 2076-3425
dc.identifier.other PURE UUID: 6a31c80e-cc02-40e3-a0a6-e709bb64a64e
dc.identifier.other PURE ITEMURL: https://research.aalto.fi/en/publications/6a31c80e-cc02-40e3-a0a6-e709bb64a64e
dc.identifier.other PURE LINK: http://www.scopus.com/inward/record.url?scp=85078285094&partnerID=8YFLogxK
dc.identifier.other PURE FILEURL: https://research.aalto.fi/files/40888379/Merzon_Temporal_Limitations.brainsci_10_00016_v2_1.pdf
dc.identifier.uri https://aaltodoc.aalto.fi/handle/123456789/43082
dc.description.abstract Itti and Koch’s Saliency Model has been used extensively to simulate fixation selection in a variety of tasks from visual search to simple reaction times. Although the Saliency Model has been tested for its spatial prediction of fixations in visual salience, it has not been well tested for their temporal accuracy. Visual tasks, like search, invariably result in a positively skewed distribution of saccadic reaction times over large numbers of samples, yet we show that the leaky integrate and fire (LIF) neuronal model included in the classic implementation of the model tends to produce a distribution shifted to shorter fixations (in comparison with human data). Further, while parameter optimization using a genetic algorithm and Nelder–Mead method does improve the fit of the resulting distribution, it is still unable to match temporal distributions of human responses in a visual task. Analysis of times for individual images reveal that the LIF algorithm produces initial fixation durations that are fixed instead of a sample from a distribution (as in the human case). Only by aggregating responses over many input images do they result in a distribution, although the form of this distribution still depends on the input images used to create it and not on internal model variability. en
dc.format.mimetype application/pdf
dc.language.iso en en
dc.publisher MDPI AG
dc.relation.ispartofseries BRAIN SCIENCES en
dc.relation.ispartofseries Volume 10, issue 1 en
dc.rights openAccess en
dc.title Temporal limitations of the standard leaky integrate and fire model en
dc.type A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä fi
dc.description.version Peer reviewed en
dc.contributor.department Department of Neuroscience and Biomedical Engineering
dc.contributor.department Werner Reichardt Centre for Integrative Neuroscience
dc.contributor.department Higher School of Economics
dc.subject.keyword Leaky integrate and fire model
dc.subject.keyword Saccade generation
dc.subject.keyword Salience model
dc.subject.keyword Visual search
dc.identifier.urn URN:NBN:fi:aalto-202002122151
dc.identifier.doi 10.3390/brainsci10010016
dc.type.version publishedVersion

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